{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/quocanhdo/Monash Uni Enterprise Dropbox/Quoc-Anh Do/Project - Network at Sciences Po/QA - Nicolo/Replication_Package/Replication_Package_Dec2025/Results/LogTable6.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}31 Dec 2025, 18:11:46
{txt}
{com}. 
. // TABLE 6: Descriptive statistics of friendships
. *** Panel A
. * probability of correct answer: meeting
. cap drop correct_meet
{txt}
{com}. gen correct_meet = 0 if LAL==1
{txt}(292,178 missing values generated)

{com}. replace correct_meet = 1 if LAL==1 & meet_i1==meet_i2 
{txt}(1,594 real changes made)

{com}. * probability of correct answer: time
. cap drop correct_time
{txt}
{com}. gen correct_time = 0 if LAL==1
{txt}(292,178 missing values generated)

{com}. replace correct_time = 1 if LAL==1 & time_i1==time_i2 
{txt}(966 real changes made)

{com}. * probability of correct answer: activity
. cap drop correct_activity
{txt}
{com}. gen correct_activity = 0 if LAL==1
{txt}(292,178 missing values generated)

{com}. replace correct_activity = 1 if LAL==1 & activity_i1==activity_i2 
{txt}(1,136 real changes made)

{com}. * probability of correct answer: strength
. cap drop correct_strength
{txt}
{com}. gen correct_strength = 0 if LAL==1
{txt}(292,178 missing values generated)

{com}. replace correct_strength = 1 if LAL==1 & strength_i1==strength_i2  
{txt}(1,062 real changes made)

{com}. * full sample
. estpost summarize fr_i1 rec correct_meet correct_time correct_activity correct_strength if uid_i1>uid_i2

{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:e(count)}{space 1}{space 1}{ralign 9:e(sum_w)}{space 1}{space 1}{ralign 9:e(mean)}{space 1}{space 1}{ralign 9:e(Var)}{space 1}{space 1}{ralign 9:e(sd)}{space 1}{space 1}{ralign 9:e(min)}{space 1}{space 1}{ralign 9:e(max)}{space 1}{space 1}{ralign 9:e(sum)}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:fr_i1}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:  8.52457}}}{space 1}{space 1}{ralign 9:{res:{sf: 4.531977}}}{space 1}{space 1}{ralign 9:{res:{sf: 2.128844}}}{space 1}{space 1}{ralign 9:{res:{sf:        3}}}{space 1}{space 1}{ralign 9:{res:{sf:       10}}}{space 1}{space 1}{ralign 9:{res:{sf:  1254416}}}{space 1}
{space 0}{space 0}{ralign 12:rec}{space 1}{c |}{space 1}{ralign 9:{res:{sf:     2309}}}{space 1}{space 1}{ralign 9:{res:{sf:     2309}}}{space 1}{space 1}{ralign 9:{res:{sf: .4608055}}}{space 1}{space 1}{ralign 9:{res:{sf: .2485714}}}{space 1}{space 1}{ralign 9:{res:{sf: .4985694}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:     1064}}}{space 1}
{space 0}{space 0}{ralign 12:correct_meet}{space 1}{c |}{space 1}{ralign 9:{res:{sf:     1064}}}{space 1}{space 1}{ralign 9:{res:{sf:     1064}}}{space 1}{space 1}{ralign 9:{res:{sf: .7490602}}}{space 1}{space 1}{ralign 9:{res:{sf: .1881459}}}{space 1}{space 1}{ralign 9:{res:{sf: .4337578}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      797}}}{space 1}
{space 0}{space 0}{ralign 12:correct_time}{space 1}{c |}{space 1}{ralign 9:{res:{sf:     1064}}}{space 1}{space 1}{ralign 9:{res:{sf:     1064}}}{space 1}{space 1}{ralign 9:{res:{sf: .4539474}}}{space 1}{space 1}{ralign 9:{res:{sf: .2481123}}}{space 1}{space 1}{ralign 9:{res:{sf: .4981088}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      483}}}{space 1}
{space 0}{space 0}{ralign 12:correct_ac~y}{space 1}{c |}{space 1}{ralign 9:{res:{sf:     1064}}}{space 1}{space 1}{ralign 9:{res:{sf:     1064}}}{space 1}{space 1}{ralign 9:{res:{sf: .5338346}}}{space 1}{space 1}{ralign 9:{res:{sf: .2490893}}}{space 1}{space 1}{ralign 9:{res:{sf: .4990885}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      568}}}{space 1}
{space 0}{space 0}{ralign 12:correct_st~h}{space 1}{c |}{space 1}{ralign 9:{res:{sf:     1064}}}{space 1}{space 1}{ralign 9:{res:{sf:     1064}}}{space 1}{space 1}{ralign 9:{res:{sf: .4990602}}}{space 1}{space 1}{ralign 9:{res:{sf: .2502343}}}{space 1}{space 1}{ralign 9:{res:{sf: .5002342}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      531}}}{space 1}

{com}. estimates store panel_a_full
{txt}
{com}. * benchmark sample
. estpost summarize fr_i1 rec correct_meet correct_time correct_activity correct_strength if $condition

{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:e(count)}{space 1}{space 1}{ralign 9:e(sum_w)}{space 1}{space 1}{ralign 9:e(mean)}{space 1}{space 1}{ralign 9:e(Var)}{space 1}{space 1}{ralign 9:e(sd)}{space 1}{space 1}{ralign 9:e(min)}{space 1}{space 1}{ralign 9:e(max)}{space 1}{space 1}{ralign 9:e(sum)}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:fr_i1}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: 8.652028}}}{space 1}{space 1}{ralign 9:{res:{sf: 3.900623}}}{space 1}{space 1}{ralign 9:{res:{sf:    1.975}}}{space 1}{space 1}{ralign 9:{res:{sf:        3}}}{space 1}{space 1}{ralign 9:{res:{sf:       10}}}{space 1}{space 1}{ralign 9:{res:{sf:   452726}}}{space 1}
{space 0}{space 0}{ralign 12:rec}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      934}}}{space 1}{space 1}{ralign 9:{res:{sf:      934}}}{space 1}{space 1}{ralign 9:{res:{sf: .4775161}}}{space 1}{space 1}{ralign 9:{res:{sf: .2497619}}}{space 1}{space 1}{ralign 9:{res:{sf: .4997618}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      446}}}{space 1}
{space 0}{space 0}{ralign 12:correct_meet}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      446}}}{space 1}{space 1}{ralign 9:{res:{sf:      446}}}{space 1}{space 1}{ralign 9:{res:{sf: .8139013}}}{space 1}{space 1}{ralign 9:{res:{sf: .1518063}}}{space 1}{space 1}{ralign 9:{res:{sf: .3896233}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      363}}}{space 1}
{space 0}{space 0}{ralign 12:correct_time}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      446}}}{space 1}{space 1}{ralign 9:{res:{sf:      446}}}{space 1}{space 1}{ralign 9:{res:{sf: .4977578}}}{space 1}{space 1}{ralign 9:{res:{sf: .2505568}}}{space 1}{space 1}{ralign 9:{res:{sf: .5005564}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      222}}}{space 1}
{space 0}{space 0}{ralign 12:correct_ac~y}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      446}}}{space 1}{space 1}{ralign 9:{res:{sf:      446}}}{space 1}{space 1}{ralign 9:{res:{sf: .5941704}}}{space 1}{space 1}{ralign 9:{res:{sf: .2416738}}}{space 1}{space 1}{ralign 9:{res:{sf: .4916033}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      265}}}{space 1}
{space 0}{space 0}{ralign 12:correct_st~h}{space 1}{c |}{space 1}{ralign 9:{res:{sf:      446}}}{space 1}{space 1}{ralign 9:{res:{sf:      446}}}{space 1}{space 1}{ralign 9:{res:{sf: .5358744}}}{space 1}{space 1}{ralign 9:{res:{sf: .2492719}}}{space 1}{space 1}{ralign 9:{res:{sf: .4992714}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      239}}}{space 1}

{com}. estimates store panel_a_benchmark
{txt}
{com}. * Create the table
. esttab panel_a_full panel_a_benchmark using "$path/Results/Table6_panel_a.tex", replace ///
>     cells("mean(fmt(3)) sd(fmt(3)) count(fmt(0))") ///
>     title("Panel B: Dyadic Dependent Variables") ///
>     mtitles("Full Sample" "Benchmark Sample") ///
>     label booktabs ///
>     addnotes("Statistics in (1) are computed on the full sample of data available for each variable," ///
>              "while statistics in (2) are computed on the benchmark sample.")
{res}{txt}(output written to {browse  `"/Users/quocanhdo/Monash Uni Enterprise Dropbox/Quoc-Anh Do/Project - Network at Sciences Po/QA - Nicolo/Replication_Package/Replication_Package_Dec2025/Results/Table6_panel_a.tex"'})

{com}. 
. *** Panel B
. sum degree_i1 if uid_i1>uid_i2, d

                   {txt}Degree for individual 1
{hline 61}
      Percentiles      Smallest
 1%    {res}        3              3
{txt} 5%    {res}        5              3
{txt}10%    {res}        7              3       {txt}Obs         {res}    147,153
{txt}25%    {res}        9              3       {txt}Sum of wgt. {res}    147,153

{txt}50%    {res}       11                      {txt}Mean          {res}  10.7645
                        {txt}Largest       Std. dev.     {res} 3.119577
{txt}75%    {res}       13             19
{txt}90%    {res}       14             19       {txt}Variance      {res} 9.731758
{txt}95%    {res}       16             19       {txt}Skewness      {res}-.1883963
{txt}99%    {res}       18             19       {txt}Kurtosis      {res} 3.185051
{txt}
{com}. scalar avg_degree = `r(mean)'
{txt}
{com}. scalar var_degree = `r(Var)'
{txt}
{com}. scalar med_degree = `r(p50)'
{txt}
{com}. scalar max_degree = `r(max)'
{txt}
{com}. scalar min_degree = `r(min)'
{txt}
{com}. 
. sum path if uid_i1>uid_i2, d

                        {txt}Shortest Path
{hline 61}
      Percentiles      Smallest
 1%    {res}        1              1
{txt} 5%    {res}        2              1
{txt}10%    {res}        2              1       {txt}Obs         {res}    147,153
{txt}25%    {res}        3              1       {txt}Sum of wgt. {res}    147,153

{txt}50%    {res}        4                      {txt}Mean          {res} 3.464571
                        {txt}Largest       Std. dev.     {res} .8296009
{txt}75%    {res}        4              6
{txt}90%    {res}        4              6       {txt}Variance      {res} .6882376
{txt}95%    {res}        5              6       {txt}Skewness      {res}-.3516452
{txt}99%    {res}        5              7       {txt}Kurtosis      {res} 3.263405
{txt}
{com}. scalar diameter = `r(max)'
{txt}
{com}. scalar avg_path = `r(mean)'
{txt}
{com}. 
. sum eigen_bonacich_cent_i1 if uid_i1>uid_i2, d

                   {txt}eigen_bonacich_cent_i1
{hline 61}
      Percentiles      Smallest
 1%    {res}  .003044       .0010574
{txt} 5%    {res} .0071889       .0010574
{txt}10%    {res} .0107766       .0010574       {txt}Obs         {res}    147,153
{txt}25%    {res} .0186871       .0010574       {txt}Sum of wgt. {res}    147,153

{txt}50%    {res} .0322421                      {txt}Mean          {res}  .035272
                        {txt}Largest       Std. dev.     {res}  .020987
{txt}75%    {res} .0474211       .1017721
{txt}90%    {res} .0662706       .1017721       {txt}Variance      {res} .0004405
{txt}95%    {res} .0767582       .1017721       {txt}Skewness      {res} .7434937
{txt}99%    {res} .0934207       .1017721       {txt}Kurtosis      {res}  3.07721
{txt}
{com}. scalar avg_eigen = `r(mean)'
{txt}
{com}. scalar std_eigen = `r(sd)'
{txt}
{com}. 
. matrix scalars_matrix = (avg_degree \ var_degree \ med_degree \ max_degree\ min_degree \ diameter \ avg_path \ avg_eigen \ std_eigen)
{txt}
{com}. matrix rownames scalars_matrix = Mean_degree Variance_degree Median_degree Max_degree Min_degree Diameter Average_pathlength Avg_eigen_centrality StdErr_eigen_centrality
{txt}
{com}. 
. estout matrix(scalars_matrix) using "$path/Results/Table6_panel_b.tex", ///
>     style(tex) replace ///
>     mlabels(none) collabels(none) ///
>     prehead("\begin{c -(}tabular{c )-}{c -(}lr{c )-}" "\toprule") ///
>     posthead("\midrule") ///
>     prefoot("\bottomrule") ///
>     postfoot("\end{c -(}tabular{c )-}")
{res}{txt}(output written to {browse  `"/Users/quocanhdo/Monash Uni Enterprise Dropbox/Quoc-Anh Do/Project - Network at Sciences Po/QA - Nicolo/Replication_Package/Replication_Package_Dec2025/Results/Table6_panel_b.tex"'})

{com}. 
. 
. *** Panel C
.         * mere relationship
. cap drop LUL1
{txt}
{com}. gen LUL1 = 0
{txt}
{com}. replace LUL1 = 1 if LULint==1
{txt}(489 real changes made)

{com}.         * firendship link
. cap drop LUL2
{txt}
{com}. gen LUL2 = 0
{txt}
{com}. replace LUL2 = 1 if LULint==2
{txt}(2,096 real changes made)

{com}.         * close firendship
. cap drop LUL3
{txt}
{com}. gen LUL3 = 0
{txt}
{com}. replace LUL3 = 1 if LULint==3
{txt}(1,209 real changes made)

{com}.         * very close friendship
. cap drop LUL4
{txt}
{com}. gen LUL4 = 0
{txt}
{com}. replace LUL4 = 1 if LULint==4
{txt}(648 real changes made)

{com}. 
. cap drop path1 path2 path3
{txt}
{com}. gen path1 = (path==1)
{txt}
{com}. gen path2 = (path==2)
{txt}
{com}. gen path3 = (path==3)
{txt}
{com}. 
. * full sample
. estpost summarize LUL path1 path2 path3 LUL1 LUL2 LUL3 LUL4 IG if uid_i1>uid_i2

{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:e(count)}{space 1}{space 1}{ralign 9:e(sum_w)}{space 1}{space 1}{ralign 9:e(mean)}{space 1}{space 1}{ralign 9:e(Var)}{space 1}{space 1}{ralign 9:e(sd)}{space 1}{space 1}{ralign 9:e(min)}{space 1}{space 1}{ralign 9:e(max)}{space 1}{space 1}{ralign 9:e(sum)}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:LUL}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf: .0156912}}}{space 1}{space 1}{ralign 9:{res:{sf:  .015445}}}{space 1}{space 1}{ralign 9:{res:{sf: .1242781}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:     2309}}}{space 1}
{space 0}{space 0}{ralign 12:path1}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf: .0156912}}}{space 1}{space 1}{ralign 9:{res:{sf:  .015445}}}{space 1}{space 1}{ralign 9:{res:{sf: .1242781}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:     2309}}}{space 1}
{space 0}{space 0}{ralign 12:path2}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf: .0930188}}}{space 1}{space 1}{ralign 9:{res:{sf: .0843669}}}{space 1}{space 1}{ralign 9:{res:{sf: .2904598}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:    13688}}}{space 1}
{space 0}{space 0}{ralign 12:path3}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf: .3802505}}}{space 1}{space 1}{ralign 9:{res:{sf: .2356617}}}{space 1}{space 1}{ralign 9:{res:{sf:   .48545}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:    55955}}}{space 1}
{space 0}{space 0}{ralign 12:LUL1}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf: .0016378}}}{space 1}{space 1}{ralign 9:{res:{sf: .0016351}}}{space 1}{space 1}{ralign 9:{res:{sf: .0404361}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      241}}}{space 1}
{space 0}{space 0}{ralign 12:LUL2}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf: .0071626}}}{space 1}{space 1}{ralign 9:{res:{sf: .0071114}}}{space 1}{space 1}{ralign 9:{res:{sf: .0843289}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:     1054}}}{space 1}
{space 0}{space 0}{ralign 12:LUL3}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf: .0041182}}}{space 1}{space 1}{ralign 9:{res:{sf: .0041012}}}{space 1}{space 1}{ralign 9:{res:{sf: .0640409}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      606}}}{space 1}
{space 0}{space 0}{ralign 12:LUL4}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf: .0021746}}}{space 1}{space 1}{ralign 9:{res:{sf: .0021699}}}{space 1}{space 1}{ralign 9:{res:{sf: .0465821}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      320}}}{space 1}
{space 0}{space 0}{ralign 12:IG}{space 1}{c |}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf:   147153}}}{space 1}{space 1}{ralign 9:{res:{sf: .0167377}}}{space 1}{space 1}{ralign 9:{res:{sf: .0164576}}}{space 1}{space 1}{ralign 9:{res:{sf: .1282873}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:     2463}}}{space 1}

{com}. estimates store panel_c_full
{txt}
{com}. * benchmark sample
. estpost summarize LUL path1 path2 path3 LUL1 LUL2 LUL3 LUL4 IG if $condition

{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:e(count)}{space 1}{space 1}{ralign 9:e(sum_w)}{space 1}{space 1}{ralign 9:e(mean)}{space 1}{space 1}{ralign 9:e(Var)}{space 1}{space 1}{ralign 9:e(sd)}{space 1}{space 1}{ralign 9:e(min)}{space 1}{space 1}{ralign 9:e(max)}{space 1}{space 1}{ralign 9:e(sum)}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:LUL}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: .0178496}}}{space 1}{space 1}{ralign 9:{res:{sf: .0175314}}}{space 1}{space 1}{ralign 9:{res:{sf:  .132406}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      934}}}{space 1}
{space 0}{space 0}{ralign 12:path1}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: .0178496}}}{space 1}{space 1}{ralign 9:{res:{sf: .0175314}}}{space 1}{space 1}{ralign 9:{res:{sf:  .132406}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      934}}}{space 1}
{space 0}{space 0}{ralign 12:path2}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: .1014601}}}{space 1}{space 1}{ralign 9:{res:{sf: .0911677}}}{space 1}{space 1}{ralign 9:{res:{sf: .3019398}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:     5309}}}{space 1}
{space 0}{space 0}{ralign 12:path3}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: .4081145}}}{space 1}{space 1}{ralign 9:{res:{sf: .2415617}}}{space 1}{space 1}{ralign 9:{res:{sf: .4914892}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:    21355}}}{space 1}
{space 0}{space 0}{ralign 12:LUL1}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: .0020449}}}{space 1}{space 1}{ralign 9:{res:{sf: .0020407}}}{space 1}{space 1}{ralign 9:{res:{sf: .0451744}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      107}}}{space 1}
{space 0}{space 0}{ralign 12:LUL2}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: .0076253}}}{space 1}{space 1}{ralign 9:{res:{sf: .0075673}}}{space 1}{space 1}{ralign 9:{res:{sf: .0869901}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      399}}}{space 1}
{space 0}{space 0}{ralign 12:LUL3}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: .0047204}}}{space 1}{space 1}{ralign 9:{res:{sf: .0046982}}}{space 1}{space 1}{ralign 9:{res:{sf: .0685435}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      247}}}{space 1}
{space 0}{space 0}{ralign 12:LUL4}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: .0031915}}}{space 1}{space 1}{ralign 9:{res:{sf: .0031814}}}{space 1}{space 1}{ralign 9:{res:{sf: .0564039}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      167}}}{space 1}
{space 0}{space 0}{ralign 12:IG}{space 1}{c |}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf:    52326}}}{space 1}{space 1}{ralign 9:{res:{sf: .0188243}}}{space 1}{space 1}{ralign 9:{res:{sf: .0184703}}}{space 1}{space 1}{ralign 9:{res:{sf: .1359055}}}{space 1}{space 1}{ralign 9:{res:{sf:        0}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:      985}}}{space 1}

{com}. estimates store panel_c_benchmark
{txt}
{com}. * Create the table
. esttab panel_c_full panel_c_benchmark using "$path/Results/Table6_panel_c.tex", replace ///
>     cells("mean(fmt(4)) sd(fmt(4)) count(fmt(0))") ///
>     title("Panel B: Dyadic Dependent Variables") ///
>     mtitles("Full Sample" "Benchmark Sample") ///
>     label booktabs ///
>     addnotes("Statistics in (1) are computed on the full sample of data available for each variable," ///
>              "while statistics in (2) are computed on the benchmark sample.")
{res}{txt}(output written to {browse  `"/Users/quocanhdo/Monash Uni Enterprise Dropbox/Quoc-Anh Do/Project - Network at Sciences Po/QA - Nicolo/Replication_Package/Replication_Package_Dec2025/Results/Table6_panel_c.tex"'})

{com}. 
. log close  // Table 6
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/quocanhdo/Monash Uni Enterprise Dropbox/Quoc-Anh Do/Project - Network at Sciences Po/QA - Nicolo/Replication_Package/Replication_Package_Dec2025/Results/LogTable6.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}31 Dec 2025, 18:11:48
{txt}{.-}
{smcl}
{txt}{sf}{ul off}